Automated technologies and novel techniques to accelerate protein crystallography for structural genomics

Recent trends in biotechnological production, engineering, and applications of lysophospholipases

Oil degumming process involves the removal of gums, which is required to improve the physicochemical and storage properties of the vegetable oils. Degumming of oils can be carried out by using chemicals, membranes (polymeric, inorganic, and ceramic), or enzymes, for example, phospholipases. Phospholipases are enzymes of tremendous significance in the degumming process as they convert gums to fatty acids and lipophilic substances. They provide a cost-effective and safe alternative to other degumming processes without affecting the oil yield. Lysophospholipases (LPLs) are highly valuable tools for degumming vegetable oils. LPLs can hydrolyze fatty acyl ester bonds of phosphatidylcholine at the sn-1 and sn-2 positions of glycerol moiety. In addition, they have the ability to catalyze hydrolysis lysophospholipids' ester bond either at sn-1 or sn-2 position. In this review, biotechnological production and biochemical characteristics of LPLs from three domains of life are highlighted. In comparison to bacterial and eukaryotic LPLs, archaeal LPLs were found to be active at high temperatures. Broad substrate specificity and thermostability of archaeal LPLs make them ideal candidates for the industrial degumming of oils. However, improvement of activity and substrate specificity of archaeal LPLs is required for enhancing their industrial utility. In the current review, various protein-engineering approaches (directed evolution, rational design, site-saturation mutagenesis, and fusion technology) as well as in silico tools have been discussed to increase the commercial significance of LPLs.

Challenges of Protein-Protein Docking of the Membrane Proteins

Despite the recent advances in the determination of high-resolution membrane protein (MP) structures, the structural and functional characterization of MPs remains extremely challenging, mainly due to the hydrophobic nature, low abundance, poor expression, purification, and crystallization difficulties associated with MPs. Whereby the major challenges/hurdles for MP structure determination are associated with the expression, purification, and crystallization procedures. Although there have been significant advances in the experimental determination of MP structures, only a limited number of MP structures (approximately less than 1% of all) are available in the Protein Data Bank (PDB). Therefore, the structures of a large number of MPs still remain unresolved, which leads to the availability of widely unplumbed structural and functional information related to MPs. As a result, recent developments in the drug discovery realm and the significant biological contemplation have led to the development of several novel, low-cost, and time-efficient computational methods that overcome the limitations of experimental approaches, supplement experiments, and provide alternatives for the characterization of MPs. Whereby the fine tuning and optimizations of these computational approaches remains an ongoing endeavor.Computational methods offer a potential way for the elucidation of structural features and the augmentation of currently available MP information. However, the use of computational modeling can be extremely challenging for MPs mainly due to insufficient knowledge of (or gaps in) atomic structures of MPs. Despite the availability of numerous in silico methods for 3D structure determination the applicability of these methods to MPs remains relatively low since all methods are not well-suited or adequate for MPs. However, sophisticated methods for MP structure predictions are constantly being developed and updated to integrate the modifications required for MPs. Currently, different computational methods for (1) MP structure prediction, (2) stability analysis of MPs through molecular dynamics simulations, (3) modeling of MP complexes through docking, (4) prediction of interactions between MPs, and (5) MP interactions with its soluble partner are extensively used. Towards this end, MP docking is widely used. It is notable that the MP docking methods yet few in number might show greater potential in terms of filling the knowledge gap. In this chapter, MP docking methods and associated challenges have been reviewed to improve the applicability, accuracy, and the ability to model macromolecular complexes.

Tagging Recombinant Proteins to Enhance Solubility and Aid Purification

Protein fusion technology has had a major impact on the efficient production and purification of individual recombinant proteins. The use of genetically engineered affinity and solubility-enhancing polypeptide "tags" has a long history, and there is a considerable repertoire of these that can be used to address issues related to the expression, stability, solubility, folding, and purification of their fusion partner. In the case of large-scale proteomic studies, the development of purification procedures tailored to individual proteins is not practicable, and affinity tags have become indispensable tools for structural and functional proteomic initiatives that involve the expression of many proteins in parallel. In this chapter, the rationale and applications of a range of established and more recently developed solubility-enhancing and affinity tags is described.

Poly-Histidine-Tagged Protein Purification Using Immobilized Metal Affinity Chromatography (IMAC)

His-tagging is the most widespread and versatile strategy used to purify recombinant proteins for biochemical and structural studies. Recombinant DNA methods are first used to engineer the addition of a short tract of poly-histidine tag (His-tag) to the N-terminus or C-terminus of a target protein. The His-tag is then exploited to enable purification of the "tagged" protein by immobilized metal affinity chromatography (IMAC). In this chapter, we describe efficient procedures for the isolation of highly purified His-tagged target proteins from an Escherichia coli host using IMAC in a bind-wash-elute strategy that can be performed under both native and denaturing conditions.

Chromatography-Free Purification Strategies for Large Biological Macromolecular Complexes Involving Fractionated PEG Precipitation and Density Gradients

A complex interplay between several biological macromolecules maintains cellular homeostasis. Generally, the demanding chemical reactions which sustain life are not performed by individual macromolecules, but rather by several proteins that together form a macromolecular complex. Understanding the functional interactions amongst subunits of these macromolecular machines is fundamental to elucidate mechanisms by which they maintain homeostasis. As the faithful function of macromolecular complexes is essential for cell survival, their mis-function leads to the development of human diseases. Furthermore, detailed mechanistic interrogation of the function of macromolecular machines can be exploited to develop and optimize biotechnological processes. The purification of intact macromolecular complexes is an essential prerequisite for this; however, chromatographic purification schemes can induce the dissociation of subunits or the disintegration of the whole complex. Here, we discuss the development and application of chromatography-free purification strategies based on fractionated PEG precipitation and orthogonal density gradient centrifugation that overcomes existing limitations of established chromatographic purification protocols. The presented case studies illustrate the capabilities of these procedures for the purification of macromolecular complexes.

3D-Printed High-Density Droplet Array Chip for Miniaturized Protein Crystallization Screening under Vapor Diffusion Mode

Here we describe the combination of three-dimensional (3D) printed chip and automated microfluidic droplet-based screening techniques for achieving massively parallel, nanoliter-scale protein crystallization screening under vapor diffusion mode. We fabricated high-density microwell array chips for sitting-drop vapor diffusion crystallization utilizing the advantage of the 3D-printing technique in producing high-aspect-ratio chips. To overcome the obstacle of 3D-printed microchips in performing long-term reactions caused by their porousness and gas permeability properties in chip body, we developed a two-step postprocessing method, including paraffin filling and parylene coating, to achieve high sealability and stability. We also developed a simple method especially suitable for controlling the vapor diffusion speed of nanoliter-scale droplets by changing the layer thickness of covering oil. With the above methods, 84 tests of nanoliter-scale protein crystallization under vapor diffusion mode were successfully achieved in the 7 × 12 droplet array chip with a protein consumption of 10 nL for each test, which is 20-100 times lower than that in the conventional large-volume screening system. Such a nanoliter-scale vapor diffusion system was applied to two model proteins with commercial precipitants and displayed advantages over that under microbatch mode. It identified more crystallization conditions, especially for the protein samples with lower concentrations.

Purification of Polyhistidine-Tagged Proteins

His-tagging is the most widespread and versatile strategy used to purify recombinant proteins for biochemical and structural studies. Recombinant DNA methods are first used to engineer the addition of a short tract of poly-histidine tag (His-tag) to the N-terminus or C-terminus of a target protein. The His-tag is then exploited to enable purification of the "tagged" protein by Immobilized Metal Affinity Chromatography (IMAC). Here, we describe efficient procedures for the isolation of highly purified His-tagged target proteins from an E. coli host using IMAC.

Advanced Methods of Protein Crystallization

This chapter provides a review of different advanced methods that help to increase the success rate of a crystallization project, by producing larger and higher quality single crystals for determination of macromolecular structures by crystallographic methods. For this purpose, the chapter is divided into three parts. The first part deals with the fundamentals for understanding the crystallization process through different strategies based on physical and chemical approaches. The second part presents new approaches involved in more sophisticated methods not only for growing protein crystals but also for controlling the size and orientation of crystals through utilization of electromagnetic fields and other advanced techniques. The last section deals with three different aspects: the importance of microgravity, the use of ligands to stabilize proteins, and the use of microfluidics to obtain protein crystals. All these advanced methods will allow the readers to obtain suitable crystalline samples for high-resolution X-ray and neutron crystallography.

Tagging Recombinant Proteins to Enhance Solubility and Aid Purification

Protein fusion technology has had a major impact on the efficient production and purification of individual recombinant proteins. The use of genetically engineered affinity and solubility-enhancing polypeptide "tags" has increased greatly in recent years and there now exists a considerable repertoire of these that can be used to solve issues related to the expression, stability, solubility, folding, and purification of their fusion partner. In the case of large-scale proteomic studies, the development of purification procedures tailored to individual proteins is not practicable, and affinity tags have therefore become indispensable tools for structural and functional proteomic initiatives that involve the expression of many proteins in parallel. Here, the rationale and applications of a range of established and more recently developed solubility-enhancing and affinity tags is described.

XPA: A key scaffold for human nucleotide excision repair

Nucleotide excision repair (NER) is essential for removing many types of DNA lesions from the genome, yet the mechanisms of NER in humans remain poorly understood. This review summarizes our current understanding of the structure, biochemistry, interaction partners, mechanisms, and disease-associated mutations of one of the critical NER proteins, XPA.

The Stanford Automated Mounter: pushing the limits of sample exchange at the SSRL macromolecular crystallography beamlines

The Stanford Automated Mounter System, a system for mounting and dismounting cryo-cooled crystals, has been upgraded to increase the throughput of samples on the macromolecular crystallography beamlines at the Stanford Synchrotron Radiation Lightsource. This upgrade speeds up robot maneuvers, reduces the heating/drying cycles, pre-fetches samples and adds an air-knife to remove frost from the gripper arms. Sample pin exchange during automated crystal quality screening now takes about 25 s, five times faster than before this upgrade.

Developments in SPR Fragment Screening

INTRODUCTION

Fragment-based approaches have played an increasing role alongside high-throughput screening in drug discovery for 15 years. The label-free biosensor technology based on surface plasmon resonance (SPR) is now sensitive and informative enough to serve during primary screens and validation steps.

AREAS COVERED

In this review, the authors discuss the role of SPR in fragment screening. After a brief description of the underlying principles of the technique and main device developments, they evaluate the advantages and adaptations of SPR for fragment-based drug discovery. SPR can also be applied to challenging targets such as membrane receptors and enzymes.

EXPERT OPINION

The high-level of immobilization of the protein target and its stability are key points for a relevant screening that can be optimized using oriented immobilized proteins and regenerable sensors. Furthermore, to decrease the rate of false negatives, a selectivity test may be performed in parallel on the main target bearing the binding site mutated or blocked with a low-off-rate ligand. Fragment-based drug design, integrated in a rational workflow led by SPR, will thus have a predominant role for the next wave of drug discovery which could be greatly enhanced by new improvements in SPR devices.

Membrane Protein Production in the Yeast, S. cerevisiae

The first crystal structures of recombinant mammalian membrane proteins were solved in 2005 using protein that had been produced in yeast cells. One of these, the rabbit Ca(2+)-ATPase SERCA1a, was synthesized in Saccharomyces cerevisiae. All host systems have their specific advantages and disadvantages, but yeast has remained a consistently popular choice in the eukaryotic membrane protein field because it is quick, easy and cheap to culture, whilst being able to post-translationally process eukaryotic membrane proteins. Very recent structures of recombinant membrane proteins produced in S. cerevisiae include those of the Arabidopsis thaliana NRT1.1 nitrate transporter and the fungal plant pathogen lipid scramblase, TMEM16. This chapter provides an overview of the methodological approaches underpinning these successes.

The synthesis of recombinant membrane proteins in yeast for structural studies

Historically, recombinant membrane protein production has been a major challenge meaning that many fewer membrane protein structures have been published than those of soluble proteins. However, there has been a recent, almost exponential increase in the number of membrane protein structures being deposited in the Protein Data Bank. This suggests that empirical methods are now available that can ensure the required protein supply for these difficult targets. This review focuses on methods that are available for protein production in yeast, which is an important source of recombinant eukaryotic membrane proteins. We provide an overview of approaches to optimize the expression plasmid, host cell and culture conditions, as well as the extraction and purification of functional protein for crystallization trials in preparation for structural studies.

ProteoPlex: stability optimization of macromolecular complexes by sparse-matrix screening of chemical space

Molecular machines or macromolecular complexes are supramolecular assemblies of biomolecules with a variety of functions. Structure determination of these complexes in a purified state is often tedious owing to their compositional complexity and the associated relative structural instability. To improve the stability of macromolecular complexes in vitro, we present a generic method that optimizes the stability, homogeneity and solubility of macromolecular complexes by sparse-matrix screening of their thermal unfolding behavior in the presence of various buffers and small molecules. The method includes the automated analysis of thermal unfolding curves based on a biophysical unfolding model for complexes. We found that under stabilizing conditions, even large multicomponent complexes reveal an almost ideal two-state unfolding behavior. We envisage an improved biochemical understanding of purified macromolecules as well as a substantial boost in successful macromolecular complex structure determination by both X-ray crystallography and cryo-electron microscopy.

Virtual screening of potential inhibitor against FtsZ protein from Staphylococcus aureus

The gram-positive bacterium Staphylococcus aureus, responsible for a wide variety of diseases in human involve all organ systems ranging from localized skin infections to life-threatening systemic infections. FtsZ, the key protein of bacterial cell division was selected as a potent anti bacterial target. In order to identify the new compounds structure based screening process was carried out. An enrichment study was performed to select a suitable scoring function and to retrieve potential candidates against FtsZ from a large chemical database. The docking score and docking energy values were compared and their atomic interaction was also evaluated. Furthermore molecular dynamics simulation were also been performed to check the stability and the amino acids interacted towards the FtsZ. Finally we selected C ID 16284, 25916, 15894, 13403 as better lead compounds. From these results, we conclude that our insilico results will provide a framework for the detailed in vitro and in vivo studies about the FtsZ protein activity in drug development process.

The role of protein structural analysis in the next generation sequencing era

Proteins are macromolecules that serve a cell’s myriad processes and functions in all living organisms via dynamic interactions with other proteins, small molecules and cellular components. Genetic variations in the protein-encoding regions of the human genome account for >85% of all known Mendelian diseases, and play an influential role in shaping complex polygenic diseases. Proteins also serve as the predominant target class for the design of small molecule drugs to modulate their activity. Knowledge of the shape and form of proteins, by means of their three-dimensional structures, is therefore instrumental to understanding their roles in disease and their potentials for drug development. In this chapter we outline, with the wide readership of non-structural biologists in mind, the various experimental and computational methods available for protein structure determination. We summarize how the wealth of structure information, contributed to a large extent by the technological advances in structure determination to date, serves as a useful tool to decipher the molecular basis of genetic variations for disease characterization and diagnosis, particularly in the emerging era of genomic medicine, and becomes an integral component in the modern day approach towards rational drug development.

Approaches to automated protein crystal harvesting

The harvesting of protein crystals is almost always a necessary step in the determination of a protein structure using X-ray crystallographic techniques. However, protein crystals are usually fragile and susceptible to damage during the harvesting process. For this reason, protein crystal harvesting is the single step that remains entirely dependent on skilled human intervention. Automation has been implemented in the majority of other stages of the structure-determination pipeline, including cloning, expression, purification, crystallization and data collection. The gap in automation between crystallization and data collection results in a bottleneck in throughput and presents unfortunate opportunities for crystal damage. Several automated protein crystal harvesting systems have been developed, including systems utilizing microcapillaries, microtools, microgrippers, acoustic droplet ejection and optical traps. However, these systems have yet to be commonly deployed in the majority of crystallography laboratories owing to a variety of technical and cost-related issues. Automation of protein crystal harvesting remains essential for harnessing the full benefits of fourth-generation synchrotrons, free-electron lasers and microfocus beamlines. Furthermore, automation of protein crystal harvesting offers several benefits when compared with traditional manual approaches, including the ability to harvest microcrystals, improved flash-cooling procedures and increased throughput.

A geometrical approach for semi-automated crystal centering andin situX-ray diffraction data collection

High-throughput protein crystallography projects pushed forward the development of automated crystallization platforms that are now commonly used. This created an urgent need for adapted and automated equipment for crystal analysis. However, first these crystals have to be harvested, cryo-protected and flash-cooled, operations that can fail or negatively impact on the crystal.In situX-ray diffraction analysis has become a valid alternative to these operations, and a growing number of users apply it for crystal screening and to solve structures. Nevertheless, even this shortcut may require a significant amount of beam time. In thisin situhigh-throughput approach, the centering of crystals relative to the beam represents the bottleneck in the analysis process. In this article, a new method to accelerate this process, by recording accurately the local geometry coordinates for each crystal in the crystallization plate, is presented. Subsequently, the crystallization plate can be presented to the X-ray beam by an automated plate-handling device, such as a six-axis robot arm, for an automated crystal centering in the beam,in situscreening or data collection. Here the preliminary results of such a semi-automated pipeline are reported for two distinct test proteins.

Recent progress in robot-based systems for crystallography and their contribution to drug discovery

INTRODUCTION

X-ray crystallography is the main tool for macromolecular structure solution at atomic resolution. It provides key information for the understanding of protein function, opening opportunities for the modulation of enzymatic mechanisms, and protein-ligand interactions. As a consequence, macromolecular crystallography plays an essential role in drug design, as well as in the a posteriori validation of drug mechanisms.

AREAS COVERED

The demand for method developments and also tools for macromolecular crystallography has significantly increased over the past 10 years. As a consequence, access to the facilities required for these investigations, such as synchrotron beamlines, became more difficult and significant efforts were dedicated to the automation of the experimental setup in laboratories. In this article, the authors describe how this was accomplished and how robot-based systems contribute to the enhancement of the macromolecular structure solution pipeline.

EXPERT OPINION

The evolution in robot technology, together with progress in X-ray beam performance and software developments, contributes to a new era in macromolecular X-ray crystallography. Highly integrated experimental environments open new possibilities for crystallography experiments. It is likely that it will also change the way this technique will be used in the future, opening the field to a larger community.

REACH: Robotic Equipment for Automated Crystal Harvesting using a six-axis robot arm and a micro-gripper

In protein crystallography experiments, only two critical steps remain manual: the transfer of crystals from their original crystallization drop into the cryoprotection solution followed by flash-cooling. These steps are risky and tedious, requiring a high degree of manual dexterity. These limiting steps are a real bottleneck to high-throughput crystallography and limit the remote use of protein crystallography core facilities. To eliminate this limit, the Robotic Equipment for Automated Crystal Harvesting (REACH) was developed. This robotized system, equipped with a two-finger micro-gripping device, allows crystal harvesting, cryoprotection and flash-cooling. Using this setup, harvesting experiments were performed on several crystals, followed by direct data collection using the same robot arm as a goniometer. Analysis of the diffraction data demonstrates that REACH is highly reliable and efficient and does not alter crystallographic data. This new instrument fills the gap in the high-throughput crystallographic pipeline.

Computational approaches to selecting and optimising targets for structural biology

Selection of protein targets for study is central to structural biology and may be influenced by numerous factors. A key aim is to maximise returns for effort invested by identifying proteins with the balance of biophysical properties that are conducive to success at all stages (e.g. solubility, crystallisation) in the route towards a high resolution structural model. Selected targets can be optimised through construct design (e.g. to minimise protein disorder), switching to a homologous protein, and selection of experimental methodology (e.g. choice of expression system) to prime for efficient progress through the structural proteomics pipeline.

Here we discuss computational techniques in target selection and optimisation, with more detailed focus on tools developed within the Scottish Structural Proteomics Facility (SSPF); namely XANNpred, ParCrys, OB-Score (target selection) and TarO (target optimisation). TarO runs a large number of algorithms, searching for homologues and annotating the pool of possible alternative targets. This pool of putative homologues is presented in a ranked, tabulated format and results are also visualised as an automatically generated and annotated multiple sequence alignment. The target selection algorithms each predict the propensity of a selected protein target to progress through the experimental stages leading to diffracting crystals. This single predictor approach has advantages for target selection, when compared with an approach using two or more predictors that each predict for success at a single experimental stage. The tools described here helped SSPF achieve a high (21%) success rate in progressing cloned targets to diffraction-quality crystals.

Getting a grip on complexes

We are witnessing tremendous advances in our understanding of the organization of life. Complete genomes are being deciphered with ever increasing speed and accuracy, thereby setting the stage for addressing the entire gene product repertoire of cells, towards understanding whole biological systems. Advances in bioinformatics and mass spectrometric techniques have revealed the multitude of interactions present in the proteome. Multiprotein complexes are emerging as a paramount cornerstone of biological activity, as many proteins appear to participate, stably or transiently, in large multisubunit assemblies. Analysis of the architecture of these assemblies and their manifold interactions is imperative for understanding their function at the molecular level. Structural genomics efforts have fostered the development of many technologies towards achieving the throughput required for studying system-wide single proteins and small interaction motifs at high resolution. The present shift in focus towards large multiprotein complexes, in particular in eukaryotes, now calls for a likewise concerted effort to develop and provide new technologies that are urgently required to produce in quality and quantity the plethora of multiprotein assemblies that form the complexome, and to routinely study their structure and function at the molecular level. Current efforts towards this objective are summarized and reviewed in this contribution.

Purification of poly-histidine-tagged proteins

His-tagging is the most widespread and versatile strategy used to purify recombinant proteins for biochemical and structural studies. Recombinant DNA methods are first used to engineer the addition of a short tract of poly-histidine tag (His-tag) to the N terminus or C terminus of a target protein. The His-tag is then exploited to enable purification of the "tagged" protein by immobilised metal affinity chromatography (IMAC). Here, we describe efficient procedures for the isolation of highly purified His-tagged target proteins from an Escherichia coli host using IMAC.

Docking methods for structure-based library design

The drug discovery process mainly relies on the experimental high-throughput screening of huge compound libraries in their pursuit of new active compounds. However, spiraling research and development costs and unimpressive success rates have driven the development of more rational, efficient, and cost-effective methods. With the increasing availability of protein structural information, advancement in computational algorithms, and faster computing resources, in silico docking-based methods are increasingly used to design smaller and focused compound libraries in order to reduce screening efforts and costs and at the same time identify active compounds with a better chance of progressing through the optimization stages. This chapter is a primer on the various docking-based methods developed for the purpose of structure-based library design. Our aim is to elucidate some basic terms related to the docking technique and explain the methodology behind several docking-based library design methods. This chapter also aims to guide the novice computational practitioner by laying out the general steps involved for such an exercise. Selected successful case studies conclude this chapter.

Tagging recombinant proteins to enhance solubility and aid purification

Protein fusion technology has enormously facilitated the efficient production and purification of individual recombinant proteins. The use of genetically engineered affinity and solubility-enhancing polypeptide "tags" has increased greatly in recent years and there now exists a considerable repertoire of these that can be used to solve issues related to the expression, stability, solubility, folding, and purification of their fusion partner. In the case of large-scale proteomic studies, the development of purification procedures tailored to individual proteins is not practicable, and affinity tags have therefore become indispensable tools for structural and functional proteomic initiatives that involve the expression of many proteins in parallel. Here, the rationale and applications of a range of established and more recently developed solubility-enhancing and affinity tags are outlined.

Replacing a reservoir solution with desiccant in vapor diffusion protein crystallization screening

This paper presents a modification to the conventional vapor diffusion (hanging- or sitting-drop) technique for protein crystallization screening. In this modified method, the reservoir solution is replaced with a desiccant to allow for a larger range of protein solution concentrations, thereby providing more opportunities for crystal formation. This method was tested in both reproducibility and screening studies, and the results showed that it significantly improves the efficiency and reduces the cost of protein crystallization screens.

EasyModeller: A graphical interface to MODELLER

BACKGROUND

MODELLER is a program for automated protein Homology Modeling. It is one of the most widely used tool for homology or comparative modeling of protein three-dimensional structures, but most users find it a bit difficult to start with MODELLER as it is command line based and requires knowledge of basic Python scripting to use it efficiently.

FINDINGS

The study was designed with an aim to develop of "EasyModeller" tool as a frontend graphical interface to MODELLER using Perl/Tk, which can be used as a standalone tool in windows platform with MODELLER and Python preinstalled. It helps inexperienced users to perform modeling, assessment, visualization, and optimization of protein models in a simple and straightforward way.

CONCLUSION

EasyModeller provides a graphical straight forward interface and functions as a stand-alone tool which can be used in a standard personal computer with Microsoft Windows as the operating system.

EasyModeller: A graphical interface to MODELLER

Background

MODELLER is a program for automated protein Homology Modeling. It is one of the most widely used tool for homology or comparative modeling of protein three-dimensional structures, but most users find it a bit difficult to start with MODELLER as it is command line based and requires knowledge of basic Python scripting to use it efficiently.

Findings

The study was designed with an aim to develop of "EasyModeller" tool as a frontend graphical interface to MODELLER using Perl/Tk, which can be used as a standalone tool in windows platform with MODELLER and Python preinstalled. It helps inexperienced users to perform modeling, assessment, visualization, and optimization of protein models in a simple and straightforward way.

Conclusion

EasyModeller provides a graphical straight forward interface and functions as a stand-alone tool which can be used in a standard personal computer with Microsoft Windows as the operating system.

To automate or not to automate: this is the question

New protocols and instrumentation significantly boost the outcome of structural biology, which has resulted in significant growth in the number of deposited Protein Data Bank structures. However, even an enormous increase of the productivity of a single step of the structure determination process may not significantly shorten the time between clone and deposition or publication. For example, in a medium size laboratory equipped with the LabDB and HKL-3000 systems, we show that automation of some (and integration of all) steps of the X-ray structure determination pathway is critical for laboratory productivity. Moreover, we show that the lag period after which the impact of a technology change is observed is longer than expected.

Binding Rate Screen - a high-throughput assay in soluble lysate for prioritizing protein expression constructs

Identification of constructs suitable for the recombinant protein production pipeline is a bottleneck for structural genomics efforts, as most methods require purified proteins and/or are labor-intensive. Here, we present a novel high-throughput approach, Binding Rate Screen, that can alleviate this bottleneck by screening expression constructs in crude soluble lysate. This functional screen utilizes the frequently employed hexahistidine (His(6)) tag as a reporter, and measures its binding rate to an affinity matrix as a metric to reflect aggregation, concentration, and purifiability of the target protein. The constructs with the highest binding rates also exhibit high expression of soluble monomeric protein as judged by analytical size-exclusion chromatography. Constructs expressing variations of the target protein can be prioritized on a time scale of minutes, which is at least 10-100 times faster than any other technologies currently available.

Towards a black-box for biological EXAFS data analysis. II. Automatic BioXAS Refinement and Analysis (ABRA)

In biological systems, X-ray absorption spectroscopy (XAS) can determine structural details of metal binding sites with high resolution. Here a method enabling an automated analysis of the corresponding EXAFS data is presented, utilizing in addition to least-squares refinement the prior knowledge about structural details and important fit parameters. A metal binding motif is characterized by the type of donor atoms and their bond lengths. These fit results are compared by bond valance sum analysis and target distances with established structures of metal binding sites. Other parameters such as the Debye-Waller factor and shift of the Fermi energy provide further insights into the quality of a fit. The introduction of mathematical criteria, their combination and calibration allows an automated analysis of XAS data as demonstrated for a number of examples. This presents a starting point for future applications to all kinds of systems studied by XAS and allows the algorithm to be transferred to data analysis in other fields.

Structural genomics approach to drug discovery for Mycobacterium tuberculosis

Structural genomics has become a powerful tool for studying microorganisms at the molecular level. Advances in technology have enabled the assembly of high-throughput pipelines that can be used to automate X-ray crystal structure determination for many proteins in the genome of a target organism. In this paper, we describe the methods used in the Tuberculosis Structural Genomics Consortium (TBSGC), ranging from protein production and crystallization to diffraction data collection and processing. The TBSGC is unique in that it uses biological importance as a primary criterion for target selection. The over-riding goal is to solve structures of proteins that may be potential drug targets, in order to support drug discovery efforts. We describe the crystal structures of several significant proteins in the M. tuberculosis genome that have been solved by the TBSGC over the past few years. We conclude by describing the high-throughput screening facilities and virtual screening facilities we have implemented for identifying small-molecule inhibitors of proteins whose structures have been solved.

Homology modeling in drug discovery: current trends and applications

As structural genomics (SG) projects continue to deposit representative 3D structures of proteins, homology modeling methods will play an increasing role in structure-based drug discovery. Although computational structure prediction methods provide a cost-effective alternative in the absence of experimental structures, developing accurate enough models still remains a big challenge. In this contribution, we report the current developments in this field, discuss in silico modeling limitations, and review the successful application of this technique to different stages of the drug discovery process.

Structures of sea anemone toxins

Sea anemones produce a variety of toxic peptides and proteins, including many ion channel blockers and modulators, as well as potent cytolysins. This review describes the structures that have been determined to date for the major classes of peptide and protein toxins. In addition, established and emerging methods for structure determination are summarized and the prospects for modelling newly described toxins are evaluated. In common with most other classes of proteins, toxins display conformational flexibility which may play a role in receptor binding and function. The prospects for obtaining atomic resolution structures of toxins bound to their receptors are also discussed.

The SWISS-MODEL Repository and associated resources

SWISS-MODEL Repository (http://swissmodel.expasy.org/repository/) is a database of 3D protein structure models generated by the SWISS-MODEL homology-modelling pipeline. The aim of the SWISS-MODEL Repository is to provide access to an up-to-date collection of annotated 3D protein models generated by automated homology modelling for all sequences in Swiss-Prot and for relevant models organisms. Regular updates ensure that target coverage is complete, that models are built using the most recent sequence and template structure databases, and that improvements in the underlying modelling pipeline are fully utilised. As of September 2008, the database contains 3.4 million entries for 2.7 million different protein sequences from the UniProt database. SWISS-MODEL Repository allows the users to assess the quality of the models in the database, search for alternative template structures, and to build models interactively via SWISS-MODEL Workspace (http://swissmodel.expasy.org/workspace/). Annotation of models with functional information and cross-linking with other databases such as the Protein Model Portal (http://www.proteinmodelportal.org) of the PSI Structural Genomics Knowledge Base facilitates the navigation between protein sequence and structure resources.